We present a unified model of the dynamics of goal-directed motivation and decision-making. The model—referred to as the GOAL architecture—provides a quantitative framework for integrating theories of goal pursuit and for relating their predictions to different types of data. The GOAL architecture proposes that motivation changes over time according to three gradients that capture the effects of the distance to the goal (i.e., the progress remaining), the time to the deadline, and the rate of progress required to achieve the goal. This enables the integration and comparison of six theoretical perspectives that make different predictions about how these dynamics unfold when pursuing approach and avoidance goals. Hierarchical Bayesian modeling was used to analyze data from three experiments which manipulate distance to goal, time to deadline, and goal type (approach vs. avoidance), and data from the naturalistic context of professional basketball. The results show that people rely on the distance and rate gradients, and to a lesser degree the time gradient, when making resource allocation decisions during goal pursuit, although the relative influence of the gradients depends on the goal type. We also demonstrate how the GOAL architecture can be used to answer questions about the influence of goal importance. Our findings suggest that goal pursuit unfolds in a complex manner that cannot be accounted for by any one previous theoretical perspective, but that is well-characterized by our unified framework. This research highlights the importance of theoretical integration for understanding motivation and decision-making during goal pursuit. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

中文翻译：

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用于对目标导向的动机和决策的动态进行建模的通用架构。

我们提出了一个统一的目标导向动机和决策动态模型。该模型（称为 GOAL 架构）提供了一个定量框架，用于整合目标追求理论并将其预测与不同类型的数据相关联。GOAL 架构提出动机根据三个梯度随时间变化，这些梯度捕获到目标的距离（即剩余进度）、截止日期的时间以及实现目标所需的进度速率。这使得能够整合和比较六个理论观点，这些观点对在追求接近和回避目标时这些动态如何展开做出不同的预测。分层贝叶斯模型用于分析来自三个实验的数据，这些实验操纵到目标的距离、到截止日期的时间、和目标类型（接近与回避），以及来自职业篮球自然背景的数据。结果表明，人们在目标追求过程中做出资源分配决策时依赖距离和速率梯度，在较小程度上依赖时间梯度，尽管梯度的相对影响取决于目标类型。我们还演示了如何使用 GOAL 架构来回答有关目标重要性影响的问题。我们的研究结果表明，目标追求以一种复杂的方式展开，以前的任何理论观点都无法解释这一点，但我们的统一框架很好地描述了这一点。这项研究强调了理论整合对于理解目标追求过程中的动机和决策的重要性。（PsycInfo 数据库记录 (c) 2021 APA，